SoulEase : AI Enhanced Personal Journal - Text Based Emotion Detection

Self-management is an art of managing your thoughts, feelings and actions that helps you achieve goals in life. In today’s expeditious world individual’s often struggle to maintain equilibrium between their personal life and work. The proposed web application uses NLP to evaluate the user behavior and mood and prepare a customized routine that balances productivity and rest by dynamically scheduling user’s tasks. Current NLP based systems for assessing behavior and mood lack the capacity for thorough and flexible scheduling. It also involves libraries like NLTK. TensorFlow is used which is a machine learning model used to personalize suggestions. The web application analyses journals entered by user using NLP and detect user’s emotions. The application gives AI generated prompts for completing their journal. When user enters their daily tasks, this application analyses the previous works of user and plan a daily schedule for them. The application also motivates them to complete their tasks by AI-generated positive affirmations through email. It analyses user’s answers of questionnaires designed for stress assessment. This model can take audio, video journaling. The web application integrates with calendar events by using google calendar API. It uses google analytics for mood tracking and analytics. The functionality of the application would be supported by strong frontend and backend architectures that make use of ReactJS for frontend and Node.js, MySQL, Firebase, for backend. The proposed app can improve sentiment analysis and it is a unique combination of different features and is expected to be 2% higher than any existing models.